- Home
- Course
- IT & Software
- Technology
- Data Science & Machine Learning with R from A-Z
Data Science & Machine Learning with R from A-Z
Overview Welcome to the immersive online course “Data Science & Machine Learning with R from A-Z.” This course is meticulously …
( 0 Reviews )
20 Students
Overview
Welcome to the immersive online course “Data Science & Machine Learning with R from A-Z.” This course is meticulously crafted to provide you with a comprehensive understanding of data science principles and machine learning techniques using the R programming language. Whether you’re a novice looking to enter the world of data science or an experienced professional aiming to expand your skill set, this course offers a structured learning path that covers everything from foundational concepts to advanced applications.
The course begins with an introduction to R programming, ensuring you grasp essential concepts such as data types, functions, and control structures. You’ll swiftly progress to data manipulation, learning how to import, clean, and preprocess datasets to prepare them for analysis. Through hands-on exercises and real-world examples, you’ll gain proficiency in using popular R packages like dplyr and tidyr for data wrangling tasks.
Moving forward, the course dives into exploratory data analysis (EDA) and data visualization using ggplot2, equipping you with techniques to uncover patterns, trends, and relationships within data. You’ll learn statistical methods for summarizing data and making informed decisions based on your analyses.
A significant focus of the course is on machine learning, where you’ll explore supervised and unsupervised learning techniques. You’ll build predictive models for regression and classification tasks, understand how to evaluate model performance using metrics like accuracy, precision, recall, and ROC curves. Techniques for handling overfitting, underfitting, and model tuning will also be covered to ensure robust and reliable predictions.
Throughout the course, you’ll work on practical projects that simulate real-world scenarios, allowing you to apply your newfound knowledge to solve complex data problems. These projects will not only reinforce your understanding but also demonstrate your ability to apply data science techniques in a meaningful way.
By the end of the course, you’ll be equipped with the skills needed to manipulate data effectively, visualize insights clearly, build predictive models confidently, and derive actionable insights from data using R. Whether you aspire to become a data scientist, machine learning engineer, or business analyst, this course will provide you with the foundation and practical experience necessary to excel in your career in data science and machine learning.
Learning Outcomes
- Master fundamental and advanced R programming concepts.
- Explore data manipulation and visualization with R.
- Build and evaluate predictive models using machine learning algorithms.
- Understand the principles of data exploration and feature engineering.
- Learn to interpret and communicate results from data analyses effectively.
What Will Make You Stand Out?
On Completion of this online course, you’ll acquire:
- CPD QS Accredited Course.
- Upon Course Completion, Earn a Complimentary PDF and a hard copy Certificate to Showcase Your Enhanced Skills.
- Lifetime access.
- 24x7 Tutor Support.
- Complete the course at your own pace.
Description
In this course, you will embark on a journey from the basics of R programming to advanced data manipulation and machine learning techniques. Starting with an introduction to R and its ecosystem, you’ll quickly progress to handling data structures, importing and cleaning datasets, and visualizing data using ggplot2. As you advance, you’ll delve into statistical analysis, hypothesis testing, and exploratory data analysis (EDA). The course will then transition into machine learning, covering regression, classification, clustering, and dimensionality reduction algorithms with practical examples in R.
Moreover, you’ll gain hands-on experience in building predictive models and assessing their performance through techniques like cross-validation and model evaluation metrics. Throughout the course, you’ll work on real-world projects that simulate industry scenarios, allowing you to apply what you’ve learned in a practical context.
By the end, you’ll have a robust understanding of how to leverage R for data science and machine learning tasks, empowering you to tackle complex data challenges and derive actionable insights from your analyses.
Who is this course for?
This course is ideal for aspiring data scientists, analysts, and professionals who want to harness the power of R for comprehensive data analysis and machine learning applications. It’s suitable for beginners with no prior experience in R or data science, as well as intermediate learners looking to deepen their understanding and practical skills in using R for data-driven decision-making.
Requirements
Access to a computer with internet connectivity and a desire to learn and succeed in your home-based business venture. No prior experience or qualifications are necessary.
Certification
Upon successful completion of the Data Science & Machine Learning with R from A-Z course, learners can obtain both a PDF certificate and a Hard copy certificate for completely FREE. The Hard copy certificate is available for a nominal fee of £3.99, which covers the delivery charge within the United Kingdom. Additional delivery charges may apply for orders outside the United Kingdom.
Career Path
- Data Scientist
- Machine Learning Engineer
- Business Analyst
Course Curriculum
| Data Science and Machine Learning Course Intro | |||
| Getting Started with R | |||
| Data Types and Structures in R | |||
| Intermediate R | |||
| Data Manipulation in R | |||
| Data Visualization in R | |||
| Creating Reports with R Markdown | |||
| Building Webapps with R Shiny | |||
| Introduction to Machine Learning | |||
| Starting A Career in Data Science | |||
| Data Science and Machine Learning Job Opportunities | 00:03:00 | ||
| Data Science and Machine Learning Introduction | 00:03:00 | ||
| What is Data Science | 00:10:00 | ||
| Machine Learning Overview | 00:05:00 | ||
| Who is This Course for | 00:03:00 | ||
| Data Science and Machine Learning Marketplace | 00:05:00 | ||
| Resources | 00:04:00 | ||
| Getting Started | 00:11:00 | ||
| Basics | 00:06:00 | ||
| Files | 00:11:00 | ||
| RStudio | 00:07:00 | ||
| Tidyverse | 00:05:00 | ||
| Vectors Part Two | 00:25:00 | ||
| Vectors – Missing Values | 00:16:00 | ||
| Vectors – Coercion | 00:14:00 | ||
| Vectors – Naming | 00:10:00 | ||
| Vectors – Misc | 00:06:00 | ||
| Creating Matrics | 00:31:00 | ||
| Introduction to Data Frames | 00:19:00 | ||
| Creating Data Frames | 00:20:00 | ||
| Data Frames: Helper Functions | 00:31:00 | ||
| Unit Introduction | 00:30:00 | ||
| Basic Type | 00:09:00 | ||
| Vector Part One | 00:20:00 | ||
| Database | 00:27:00 | ||
| Data Import or Export | 00:22:00 | ||
| Two Variable Plots | 00:21:00 | ||
| Facets, Layering, and Coordinate Systems | 00:18:00 | ||
| Styling and Saving | 00:12:00 | ||
| Data Visualization in R Section Intro | 00:17:00 | ||
| Getting Started | 00:16:00 | ||
| Aesthetics Mappings | 00:25:00 | ||
| Creating with R Markdown | 00:29:00 | ||
| Other Examples with R Shiny | 00:34:00 | ||
| Introduction to R Shiny | 00:26:00 | ||
| A Basic R Shiny App | 00:31:00 | ||
| Machine Learning Part 2 | 00:47:00 | ||
| Machine Learning Part 1 | 00:22:00 | ||
| Starting a Data Science Career Section Overview | 00:03:00 | ||
| Networking Do’s and Don’ts | 00:04:00 | ||
| Data Science Resume | 00:04:00 | ||
| Getting Started with Freelancing | 00:05:00 | ||
| Top Freelance Websites | 00:05:00 | ||
| Personal Branding | 00:05:00 | ||
| Importance of Website and Blo | 00:04:00 | ||
| DSand ML Course Sales Video | 00:04:00 | ||
| 17DATA~1 | 00:04:00 | ||
| Data Frames: Tibbles | 00:39:00 | ||
| List | 00:32:00 | ||
| Loops | 00:08:00 | ||
| Functions | 00:14:00 | ||
| Packages | 00:11:00 | ||
| Factors | 00:28:00 | ||
| Dates and Times | 00:30:00 | ||
| Functional Programming | 00:37:00 | ||
| Intermediate Introduction | 00:47:00 | ||
| Relational Operations | 00:11:00 | ||
| Logical Operators | 00:07:00 | ||
| Conditional Statements | 00:11:00 | ||
| The Arrange Verb | 00:10:00 | ||
| The Summarize Verb | 00:23:00 | ||
| Data Pivoting | 00:43:00 | ||
| JSON Parsing | 00:11:00 | ||
| String Manipulation | 00:33:00 | ||
| Web Scraping | 00:59:00 | ||
| Tidy Data | 00:11:00 | ||
| The Pipe Operator | 00:15:00 | ||
| The Filter Verb | 00:22:00 | ||
| The Select Verb | 00:46:00 | ||
| The Mutate Verb | 00:32:00 | ||
| Single Variable Plots | 00:37:00 | ||
| Data Manipulation Section Intro | 00:36:00 | ||
Frequently Asked Questions
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
In the UK, the social care system is mainly managed by the local councils. People are directly employed by the councils. They often work together with the health commissioners under joint funding arrangements. Some people work for private companies or voluntary organizations hired by local councils. They help the local councils with their personal social services.
14-Day Money-Back Guarantee
-
Number of Units:
72 -
Access:
1 Year -
Duration:
22 hours, 22 minutes -
PDF Certificate
Included
https://discovertraining.net/wp-content/uploads/2022/05/discover-training-logo.webp
COPYRIGHT © 2021 One Education
Oops! We could not locate your form.